from dataclasses import dataclass, field
from typing import Optional

from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser




@dataclass
class   _UpperCamelCase :


			"""simple docstring"""






			__a    :					str     					=		field(
			    metadata={'''help''': '''The output directory where the model will be written.'''}		,)
			__a    :					str     					=		field(
			    metadata={
			        '''help''': (
			            '''The encoder model checkpoint for weights initialization.'''
			            '''Don\'t set if you want to train an encoder model from scratch.'''
			        )
			    }		,)
			__a    :					str     					=		field(
			    metadata={
			        '''help''': (
			            '''The decoder model checkpoint for weights initialization.'''
			            '''Don\'t set if you want to train a decoder model from scratch.'''
			        )
			    }		,)
			__a    :					Optional[str]     					=		field(
			    default=_UpperCAmelCase		,metadata={'''help''': '''Pretrained encoder config name or path if not the same as encoder_model_name'''}					)
			__a    :					Optional[str]     					=		field(
			    default=_UpperCAmelCase		,metadata={'''help''': '''Pretrained decoder config name or path if not the same as decoder_model_name'''}					)





def 							UpperCAmelCase		(       ):







				"""simple docstring"""



				__lowercase					     =				HfArgumentParser((ModelArguments,)				)
				((__lowercase)     ,	)					     =				parser.parse_args_into_dataclasses()

				# Load pretrained model and tokenizer

				# Use explicit specified encoder config
				if model_args.encoder_config_name:
								__lowercase					     =				AutoConfig.from_pretrained(model_args.encoder_config_name				)
				# Use pretrained encoder model's config
				else:
								__lowercase					     =				AutoConfig.from_pretrained(model_args.encoder_model_name_or_path				)

				# Use explicit specified decoder config
				if model_args.decoder_config_name:
								__lowercase					     =				AutoConfig.from_pretrained(model_args.decoder_config_name				)
				# Use pretrained decoder model's config
				else:
								__lowercase					     =				AutoConfig.from_pretrained(model_args.decoder_model_name_or_path				)

				# necessary for `from_encoder_decoder_pretrained` when `decoder_config` is passed
				__lowercase					     =				True
				__lowercase					     =				True

				__lowercase					     =				FlaxVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
				    encoder_pretrained_model_name_or_path=model_args.encoder_model_name_or_path				,     decoder_pretrained_model_name_or_path=model_args.decoder_model_name_or_path				,     encoder_config=lowercase				,     decoder_config=lowercase				,     )

				# GPT2 only has bos/eos tokens but not decoder_start/pad tokens
				__lowercase					     =				decoder_config.decoder_start_token_id
				__lowercase					     =				decoder_config.pad_token_id
				if decoder_start_token_id is None:
								__lowercase					     =				decoder_config.bos_token_id
				if pad_token_id is None:
								__lowercase					     =				decoder_config.eos_token_id

				# This is necessary to make Flax's generate() work
				__lowercase					     =				decoder_config.eos_token_id
				__lowercase					     =				decoder_start_token_id
				__lowercase					     =				pad_token_id

				__lowercase					     =				AutoImageProcessor.from_pretrained(model_args.encoder_model_name_or_path				)

				__lowercase					     =				AutoTokenizer.from_pretrained(model_args.decoder_model_name_or_path				)
				__lowercase					     =				tokenizer.convert_ids_to_tokens(model.config.pad_token_id				)

				model.save_pretrained(model_args.output_dir				)
				image_processor.save_pretrained(model_args.output_dir				)
				tokenizer.save_pretrained(model_args.output_dir				)


if __name__ == "__main__":
		main()
from argparse import ArgumentParser

from .env import EnvironmentCommand





def 							UpperCAmelCase		(       ):







				"""simple docstring"""



				__lowercase					     =				ArgumentParser('''Diffusers CLI tool'''				,     usage='''diffusers-cli <command> [<args>]'''				)
				__lowercase					     =				parser.add_subparsers(help='''diffusers-cli command helpers'''				)

				# Register commands
				EnvironmentCommand.register_subcommand(lowercase				)

				# Let's go
				__lowercase					     =				parser.parse_args()

				if not hasattr(lowercase				,     '''func'''				):
								parser.print_help()
								exit(1				)

				# Run
				__lowercase					     =				args.func(lowercase				)
				service.run()


if __name__ == "__main__":
		main()